One of the fundamental problems of digital information is how to effectively sort through tremendous volumes of data, in order to find those pieces of information which are most relevant, at any given time. Search engines include a relevance or ranking function, in order to address this issue. These relevance functions are used to give differing weights to documents which needs the search criteria; the weights, or ranks, assigned can then be used to further manipulate the pool of information, e.g., by displaying results in a certain order.
Many search engines, particularly those used for interaction with databases, use some variation on a tf-idf weight scheme, where the frequency of the occurrence of a term in a particular document is weighed against the inverse document frequency, a measure of how often the term appears in the pool of documents. Different search engines will implement different variations on the scheme, with the individual search engine optimized to use its particular relevance function.